A Programming Model for Portable Fault Detection and Diagnosis

Dimitri Mavrokapnidis, Gabe Fierro, I. Korolija, D. Rovas
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引用次数: 2

Abstract

Portable applications support the write once, deploy everywhere paradigm. This paradigm is particularly attractive in building applications, where current practice involves the manual deployment and configuration of such applications, requiring significant engineering effort and concomitant costs. This is a tedious and error-prone process which does not scale well. Notwithstanding recent advances in semantic data modelling that allow a unified representation of buildings, we still miss a paradigm for deploying portable building applications at scale. This paper introduces a portable programming model for such applications, which we examine in the context of Fault-Detection and Diagnosis (FDD). In particular, we look at the separation of the FDD logic and the configuration with specific data inputs. We architect a software system that enables their self-configuration and execution across various building configurations, expressed in terms of Brick metadata models. Our initial results from authoring and executing APAR (AHU Performance Assessment Rules) on multiple AHUs of two museums demonstrate the potential of our model to reduce repetitive tasks and deployment costs of FDD applications.
便携式故障检测与诊断的编程模型
可移植应用程序支持一次写入,随处部署的范例。这种范例在构建应用程序时特别有吸引力,因为当前的实践涉及到手工部署和配置这样的应用程序,需要大量的工程工作和伴随的成本。这是一个冗长且容易出错的过程,而且不能很好地扩展。尽管最近在语义数据建模方面取得了进展,允许对建筑物进行统一表示,但我们仍然缺少大规模部署便携式建筑应用程序的范例。本文介绍了一种用于此类应用的可移植编程模型,并在故障检测和诊断(FDD)的背景下对其进行了研究。特别地,我们将研究FDD逻辑和具有特定数据输入的配置的分离。我们构建了一个软件系统,使其能够在各种建筑配置中进行自我配置和执行,这些配置用Brick元数据模型表示。我们在两个博物馆的多个AHU上编写和执行APAR (AHU性能评估规则)的初步结果证明了我们的模型在减少FDD应用程序的重复任务和部署成本方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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